Ryan Wisnesky

Effective interactive proofs for higher-order imperative programs

We present a new approach for constructing and verifying higher-order, imperative programs using the Coq proof assistant. We build on the past work on the Ynot system, which is based on Hoare Type Theory. That original system was a proof of concept, where every program verification was accomplished via laborious manual proofs, with much code devoted to uninteresting low-level details. In this paper, we present a re-implementation of Ynot which makes it possible to implement fully-verified, higher-order imperative programs with reasonable proof burden. At the same time, our new system is implemented entirely in Coq source files, showcasing the versatility of that proof assistant as a platform for research on language design and verification. Both versions of the system have been evaluated with case studies in the verification of imperative data structures, such as hash tables with higher-order iterators. The verification burden in our new system is reduced by at least an order of magnitude compared to the old system, by replacing manual proof with automation. The core of the automation is a simplification procedure for implications in higher-order separation logic, with hooks that allow programmers to add domain-specific simplification rules. We argue for the effectiveness of our infrastructure by verifying a number of data structures and a packrat parser, and we compare to similar efforts within other projects. Compared to competing approaches to data structure verification, our system includes much less code that must be trusted; namely, about a hundred lines of Coq code defining a program logic. All of our theorems and decision procedures have or build machine-checkable correctness proofs from first principles, removing opportunities for tool bugs to create faulty verifications.

Orchid: Integrating Schema Mapping and ETL

This paper describes Orchid, a system that converts declarative mapping specifications into data flow specifications (ETL jobs) and vice versa. Orchid provides an abstract operator model that serves as a common model for both transformation paradigms; both mappings and ETL jobs are transformed into instances of this common model. As an additional benefit, instances of this common model can be optimized and deployed into multiple target environments. Orchid is being deployed in FastTrack, a data transformation toolkit in IBM Information Server.

Toward a verified relational database management system

We report on our experience implementing a lightweight, fully verified relational database management system (RDBMS). The functional specification of RDBMS behavior, RDBMS implementation, and proof that the implementation meets the specification are all written and verified in Coq. Our contributions include: (1) a complete specification of the relational algebra in Coq; (2) an efficient realization of that model (B+ trees) implemented with the Ynot extension to Coq; and (3) a set of simple query optimizations proven to respect both semantics and run-time cost. In addition to describing the design and implementation of these artifacts, we highlight the challenges we encountered formalizing them, including the choice of representation for finite relations of typed tuples and the challenges of reasoning about data structures with complex sharing. Our experience shows that though many challenges remain, building fully-verified systems software in Coq is within reach.

HIL: a high-level scripting language for entity integration

We introduce HIL, a high-level scripting language for entity resolution and integration. HIL aims at providing the core logic for complex data processing flows that aggregate facts from large collections of structured or unstructured data into clean, unified entities. Such flows typically include many stages of processing that start from the outcome of information extraction and continue with entity resolution, mapping and fusion. A HIL program captures the overall integration flow through a combination of SQL-like rules that link, map, fuse and aggregate entities. A salient feature of HIL is the use of logical indexes in its data model to facilitate the modular construction and aggregation of complex entities. Another feature is the presence of a flexible, open type system that allows HIL to handle input data that is irregular, sparse or partially known. As a result, HIL can accurately express complex integration tasks, while still being high-level and focused on the logical entities (rather than the physical operations). Compilation algorithms translate the HIL specification into efficient run-time queries that can execute in parallel on Hadoop. We show how our framework is applied to real-world integration of entities in the financial domain, based on public filings archived by the U.S. Securities and Exchange Commission (SEC). Furthermore, we apply HIL on a larger-scale scenario that performs fusion of data from hundreds of millions of Twitter messages into tens of millions of structured entities.

Trace-based verification of imperative programs with I/O

In this paper we demonstrate how to prove the correctness of systems implemented using low-level imperative features like pointers, files, and socket I/O with respect to high level I/O protocol descriptions by using the Coq proof assistant. We present a web-based course gradebook application developed with Ynot, a Coq library for verified imperative programming. We add a dialog-based I/O system to Ynot, and we extend Ynots underlying Hoare logic with event traces to reason about I/O and protocol behavior. Expressive abstractions allow the modular verification of both high level specifications like privacy guarantees and low level properties like data structure pointer invariants.

High-Level Rules for Integration and Analysis of Data: New Challenges

Data integration remains a perenially difficult task. The need to access, integrate and make sense of large amounts of data has, in fact, accentuated in recent years. There are now many publicly available sources of data that can provide valuable information in various domains. Concrete examples of public data sources include: bibliographic repositories (DBLP, Cora, Citeseer), online movie databases (IMDB), knowledge bases (Wikipedia, DBpedia, Freebase), social media data (Facebook and Twitter, blogs). Additionally, a number of more specialized public data repositories are starting to play an increasingly important role. These repositories include, for example, the U.S. federal government data, congress and census data, as well as financial reports archived by the U.S. Securities and Exchange Commission (SEC).

Mapping polymorphism

We examine schema mappings from a type-theoretic perspective and aim to facilitate and formalize the reuse of mappings. Starting with the mapping language of Clio, we present a type-checking algorithm such that typable mappings are necessarily satisfiable. We add type variables to the schema language and present a theory of polymorphism, including a sound and complete type inference algorithm and a semantic notion of a principal type of a mapping. Principal types, which intuitively correspond to the minimum amount of schema structure required by the mappings, have an important application for mapping reuse. Concretely, we show that mappings can be reused, with the same semantics, on any schemas as long as these schemas are expansions (i.e., subtypes) of the principal types.

Algebraic Model Management: A Survey

We survey the field of model management and describe a new model management approach based on algebraic specification.